In this activity, you will use the Interactive Atmospheric Data Visualization tools of NOAA's Earth System Research Laboratory to create some plots of climate data that interest you.
Part 1: Visualize your own climate data
Create a word processing document (Microsoft Word, Macintosh Pages, Google Docs, or PDF) to record your work for this problem set.
Paste your plots into your document, and answer these questions.
- Where are your stations and what type of data collection do they employ? (i.e., how far above sea level? surface? airplane? tower?)
- Compare your time series plots of CO2 to that of Mauna Loa in a few sentences. Are the ambient levels of CO2 today the same or different at each of the three stations? Is the change per year about the same or different? Is CO2 level rising faster / slower / at the same rate at your stations compared to Mauna Loa?
- What is the seasonal variability of CO2 at your stations compared to that at Mauna Loa? (You can see the average seasonal pattern better by choosing the "seasonal patterns" option when you make your plot.)
- Compare your time series plots of CH4 to that of Mauna Loa in a few sentences. Are the ambient levels of CH4 today the same or different? Is the change per year about the same or different? Is CH4 level rising faster / slower / at the same rate at your stations compared to Mauna Loa?
- What is the seasonal variability of CH4 at your stations compared to that at Mauna Loa? (You can see the average seasonal pattern better by choosing the "seasonal patterns" option when you make your plot.)
- A well-mixed atmosphere is one that is basically homogenous with respect to gas concentrations on short timescales (less than a year). If our atmosphere is well-mixed, it means that regardless of the locations of the sources of the greenhouse gas emissions, all parts of the world have about the same level of greenhouse gas concentrations. Based on this exercise, is our atmosphere well-mixed with regard to carbon dioxide and methane? (Feel free to check out a few more stations to verify your answer.)
- Before the Industrial Revolution, the concentration of carbon dioxide in the atmosphere was about 270 parts per million. Many climate scientists have hypothesized that the present climate conditions for which our species is adapted will deteriorate significantly and irrevocably if the atmospheric concentration of carbon dioxide doubles from its pre-industrial level. If the current average rate of increase of carbon dioxide concentration you have observed at your three stations remains the same, when will atmospheric carbon dioxide double its concentration from pre-industrial times?
Part 2: Bad cherrypicking of good data
People often wonder how there can be different interpretations of the same datasets. In Part 2 of this activity, we will deliberately set up a "strawman" of a dataset that has been selected to maximize the potential for incorrect interpretation in order to see how different interpretations can arise. To do this we will take advantage of the fact that there is natural variability in the concentration of CO2 in the atmosphere due to the seasonality of plant growth. We will make two plots, each containing several months of data at Mauna Loa.
Answer the following questions on your document:
- Look at the Octoberto May plot. If you had never seen the full range of data spanning multiple decades, what might you conclude from this plot?
- Look at the Juneto October plot. If you had never seen the full range of data spanning multiple decades, what might you conclude from this plot?
- Why is it so important to sample the atmosphere continuously and for a long period of time?
- What are some of the points raised in this problem set that do not lend themselves to simple table-top experiments in a lab or a classroom?
Submitting your work
Upload your document to the "Lesson 5 - Keeling curve problem set" assignment in CANVAS by the due date indicated on the first page of this lesson. Here's what should be in your document: 4 plots from part 1 and the answers to the part 1 questions; two plots from part 2 and answers to the part 2 questions. Name your document like this:
For example, Cardinals second baseman Kolten Wong would name his problem set L5_keelingcurve_kkw16_wong.doc
I will use my general rubric for grading problem sets to grade this activity.